Risk evaluation of highway merging conflict areas incorporating emergency vehicle priority passage

Highway merging areas are critical safety hotspots where traffic conflicts arise from competing demands for gap acceptance, speed adaptation, and lateral maneuvering. These inherent risks can be further exacerbated when emergency vehicles are granted priority passage, introducing abrupt and spatially localized disturbances that existing risk assessment approaches are not well-suited to capture. Current safety evaluation methods for merging areas generally fall into two categories. The first comprises surrogate safety approaches based on traffic conflicts, which require dense sensing infrastructure and continuous microscopic vehicle trajectory data. The second includes statistical approaches based on historical crash records, which suffer from temporal lag and are unable to reflect real-time risk dynamics. Neither category adequately captures the transient and stochastic disturbances induced by emergency vehicle operations. To address this gap, this study develops a risk evaluation framework for highway merging conflict areas that explicitly incorporates the stochastic arrival and priority passage of emergency vehicles.

The merging area is discretized into grid cells to facilitate spatially explicit risk assessment. A comprehensive conflict index (CI) is developed by integrating a near-collision-based conflict probability model with a kinetic-energy-based conflict severity model, thereby capturing both the likelihood and potential consequences of hazardous interactions. The framework explicitly considers the stochastic arrival patterns and priority operations of emergency vehicles. Model calibration and validation are conducted using real-world vehicle trajectory data obtained from drone observations at a highway merging segment in Guangzhou, China. Sensitivity analyses are further performed with respect to emergency vehicle speed, traffic demand, heavy vehicle proportion, and conflict time threshold.

High CI values consistently concentrate near the merging point, identifying this location as a persistent spatial hotspot for targeted safety intervention. The priority passage of emergency vehicles significantly elevates conflict risk, although its impact remains largely localized in both space and time. Increases in traffic demand, heavy vehicle proportion, and conflict time threshold further amplify both the magnitude and spatial extent of risk.

Safety interventions should prioritize the critical spatiotemporal window surrounding emergency vehicle entry and the subsequent merging process. Because the proposed framework primarily relies on meso-level traffic flow parameters rather than continuous high-resolution vehicle state data, it is well-suited for environments with sparse sensor deployment. The framework provides a practical and scalable tool for proactive safety assessment and supports early-stage planning and operational decision-making in highway merging areas.